IEnumerable<Connection> GetNeuronConnections(Link[] prior,NeuronBase neuron, Bias bias)
{
foreach(Link link in prior)
yield return new Connection(link,neuron);
if(bias!=null)
yield return new Connection(bias,neuron);
}
public Connection(Weight weight,Link previous,NeuronBase next)
{
Utility.Verify(()=> weight!=null && previous!=null && next!=null);
Weight=weight;
Next=next;
Previous=previous;
}
public override void Connect(Link[] prior,NeuronBase[] next,Bias bias)
{
Utility.Verify(prior,x => x!=null && prior.Length>0,"Invalid prior layer");
Utility.Verify(next,x => x!=null && next.Length>0,"Invalid next layer");
Utility.Verify(() => next.Length % FeatureMapsCount==0,"FeatureMapsCount - next layer size conflict");
Utility.Verify(() => prior.Length % FeatureMapsCount==0,"FeatureMapsCount - prior layer size conflict");
Link[][] c=GetFeatureMaps(prior,FeatureMapsCount);
NeuronBase[][] s=GetFeatureMaps(next,FeatureMapsCount);
Link[][][] kernelCollection=GetKernelCollection(c,2,0); //always x/2
Dictionary<Link,List<Connection>> map=new Dictionary<Link,List<Connection>>();
for(var i=0;i<kernelCollection.Length;i++)
ConnectFeatureMaps(s[i],kernelCollection[i],bias,map);
foreach(Link link in prior)
link.Next= map[link].ToArray();
foreach(NeuronBase neuron in next)
neuron.Previous=map[neuron].ToArray();
if(bias!=null){
if(bias.Next==null)
bias.Next=new Connection[] { };
bias.Next=bias.Next.Concat(map[bias]).ToArray();
}
}
public Connection(Weight weight, Link previous, NeuronBase next)
{
Utility.Verify(() => weight != null && previous != null && next != null);
Weight = weight;
Next = next;
Previous = previous;
}
void ConnectFeatureMaps(NeuronBase[] next,Link[][] kernelCollection,Bias bias,Dictionary<Link,List<Connection>> map)
{
SharedWeight weight=new SharedWeight(next.Length);
SharedWeight biasWeight=new SharedWeight(next.Length);
for(var i=0;i<kernelCollection.Length;i++){
ConnectKernel(next[i],kernelCollection[i],weight,map);
if(bias!=null){
Map(bias,next[i],biasWeight,map);
}
}
}
void CheckConnection(Link pre, NeuronBase post,ref int i)
{
var bridge= from a in pre.Next join b in post.Previous on a equals b select a;
Assert.AreEqual(bridge.Count(),1);
Connection inp=bridge.First();
Assert.AreEqual(inp.Previous,pre);
Assert.AreEqual(inp.Next,post);
i++;
if(post.Next!=null){
foreach(var n in post.Next) {
var pp=n.Next;
CheckConnection(post,pp,ref i);
}
}
}
public override void Connect(Link[] prior,NeuronBase[] next,Bias bias)
{
Utility.Verify(prior,x => x!=null && prior.Length>0,"Invalid prior layer");
Utility.Verify(next,x => x!=null && next.Length>0,"Invalid next layer");
foreach(NeuronBase neuron in next)
neuron.Previous=GetNeuronConnections(prior,neuron,bias).ToArray();
int idx=0;
foreach(Link link in prior)
link.Next=GetLinkConnections(idx++,next).ToArray();
if(bias!=null){
var biasConnections=GetBiasConnections(bias,next);
if(bias.Next==null)
bias.Next=new Connection[] { };
bias.Next=bias.Next.Concat(biasConnections).ToArray();
}
}
public override void Connect(Link[] prior,NeuronBase[] next,Bias bias)
{
Utility.Verify(prior,x => x!=null && prior.Length>0,"Invalid prior layer");
Utility.Verify(next,x => x!=null && next.Length>0,"Invalid next layer");
Utility.Verify(() => next.Length % NextFeatureMapsCount==0,"NextFeatureMapsCount - next layer size conflict");
Utility.Verify(() => prior.Length % PriorFeatureMapsCount==0,"PriorFeatureMapsCount - prior layer size conflict");
Link[][] fmp=GetFeatureMaps(prior,PriorFeatureMapsCount);
Link[][] fmn=GetFeatureMaps(next,NextFeatureMapsCount);
Link[][][] kernelCollection=GetKernelCollection(fmp,KernelSize,Overlap);
Dictionary<Link,List<Connection>> map=new Dictionary<Link,List<Connection>>();
for(int f=0;f<fmn.Length;f++) {
Neuron[] nextFeatureMap=fmn[f].Select(x => (Neuron)x).ToArray();
for(int p=0;p<fmp.Length;p++) {
bool inSchema=Schema[p][f];
if(inSchema)
ConnectFeatureMaps(nextFeatureMap,kernelCollection[p],map);
}
if(bias!=null) {
Weight weight=new SharedWeight(nextFeatureMap.Length);
foreach(Neuron node in nextFeatureMap)
Map(bias,node,weight,map);
}
}
foreach(Link link in prior)
link.Next= map[link].ToArray();
foreach(Neuron node in next)
node.Previous=map[node].ToArray();
if(bias!=null){
if(bias.Next==null)
bias.Next=new Connection[] { };
bias.Next=bias.Next.Concat(map[bias]).ToArray();
}
}
public Connection(Link previous,NeuronBase next)
: this(new Weight(),previous,next)
{
}
void ConnectKernel(NeuronBase neuron,Link[] kernel,SharedWeight weight,Dictionary<Link,List<Connection>> map)
{
foreach(Link link in kernel) {
Map(link,neuron,weight,map);
}
}
public Connection(Link previous, NeuronBase next)
: this(new Weight(), previous, next)
{
}
public abstract void Connect(Link[] prior,NeuronBase[] next, Bias bias);
IEnumerable<Connection> GetLinkConnections(int index,NeuronBase[] next)
{
foreach(NeuronBase neuron in next)
yield return neuron.Previous[index];
}
IEnumerable<Connection> GetBiasConnections(Bias bias, NeuronBase[] next)
{
foreach(NeuronBase neuron in next)
yield return neuron.Previous[neuron.Previous.Length-1];
}
